Social Context and the Pathways to Happiness

Quantitative studies of human happiness often assume that the determinants of happiness are universal across time and place, reflecting inherent psychological needs. This dissertation challenges this assumption, exploring the idea that the determinants of happiness vary across social contexts. Chapter one tests the hypothesis that relationship between religiosity and happiness depends upon economic conditions; chapter two examines the impact of unemployment on happiness across four countries; chapter three explores the impact of private sector employment on happiness against the backdrop of the Chinese market reforms. Taken together, the findings suggest that researchers seeking to better understand the determinants of happiness should account for the moderating effects of social conditions

Revisiting Class-Based Affirmative Action in Government Contracting

The Article highlights the existing class-based alternatives to affirmative action in government contracting based on races in the U.S. in 2011. It discusses the theory of class-based affirmative action, state-by-state anti-affirmative action movement and the history of affirmative action. It explores three programs aimed to encourage the development of job in disadvantaged areas by government contracting and show the ways on how each program is structured

On Similarities between Inference in Game Theory and Machine Learning

In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two domains so as to facilitate developments at the intersection of both fields, and as proof of the usefulness of this approach, we use recent developments in each field to make useful improvements to the other. More specifically, we consider the analogies between smooth best responses in fictitious play and Bayesian inference methods. Initially, we use these insights to develop and demonstrate an improved algorithm for learning in games based on probabilistic moderation. That is, by integrating over the distribution of opponent strategies (a Bayesian approach within machine learning) rather than taking a simple empirical average (the approach used in standard fictitious play) we derive a novel moderated fictitious play algorithm and show that it is more likely than standard fictitious play to converge to a payoff-dominant but risk-dominated Nash equilibrium in a simple coordination game. Furthermore we consider the converse case, and show how insights from game theory can be used to derive two improved mean field variational learning algorithms. We first show that the standard update rule of mean field variational learning is analogous to a Cournot adjustment within game theory. By analogy with fictitious play, we then suggest an improved update rule, and show that this results in fictitious variational play, an improved mean field variational learning algorithm that exhibits better convergence in highly or strongly connected graphical models. Second, we use a recent advance in fictitious play, namely dynamic fictitious play, to derive a derivative action variational learning algorithm, that exhibits superior convergence properties on a canonical machine learning problem (clustering a mixture distribution)

Consolidated bibliography of military and civilian studies in personnel retention and job turnover

Working Paper Serieshttp://archive.org/details/consolidatedbibl35reecNAN

Dr. Robert D. Reece interview (1) conducted on October 31, 1984 about the Boonshoft School of Medicine at Wright State University

This is the first in a series of interviews with Dr. Robert D. Reece, founding Chairman of the Department of Medicine in Society in the Wright State School of Medicine. In this first interview, Dr. Reece discusses the early development of the department and how it impacts the medical student. In the first part of the interview Dr. Reece discusses his education and background prior to coming to Wright State University. He also recalls the discussions leading to the establishment of the Department of Medicine in Society within the School of Medicine. Dr. Reece then examines the development of the department, focusing on his priorities of curriculum and staff development. In the second part of the interview Dr. Reece discusses the curriculum of the department and how the department impacts the medical student. Elements of the curriculum discussed in detail are: the core courses of the department; the department\u27s selectives; and department participation in correlation sessions and grand rounds

The Resurgence of the Highly Ylidic N‐Heterocyclic Olefins as a New Class of Organocatalysts

In recent decades, N‐heterocyclic carbenes have become established as a prevalent family of organocatalysts. N‐Heterocyclic olefins, the alkylidene derivatives of N‐heterocyclic carbenes, have recently also emerged as efficient promoters for CO2 fixation and polymerization reactions. Their extraordinarily strong Lewis/Brønsted basicity suggests great potential as a new class of organocatalysts for a broad range of reactions in synthetic chemistry.One carbon better: N‐Heterocyclic olefins, the alkylidene derivatives of the prevalent N‐heterocyclic carbenes, have recently emerged as efficient promoters for CO2 fixation and polymerization reactions. Their extraordinarily strong Lewis/Brønsted basicity suggests great potential as a new class of organocatalysts for a broad range of reactions in synthetic chemistry.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137526/1/chem201503575_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137526/2/chem201503575.pd